HDAC4 promotes nasopharyngeal carcinoma progression and serves as a therapeutic target
Bibliographic record
Abstract
Histone deacetylases (HDACs) are involved in tumor progression, and some have been successfully targeted for cancer therapy. The expression of histone deacetylase 4 (HDAC4), a class IIa HDAC, was upregulated in our previous microarray screen. However, the role of HDAC4 dysregulation and mechanisms underlying tumor growth and metastasis in nasopharyngeal carcinoma (NPC) remain elusive. Here, we first confirmed that the HDAC4 levels in primary and metastatic NPC tissues were significantly increased compared with those in normal nasopharyngeal epithelial tissues and found that high HDAC4 expression predicted a poor overall survival (OS) and progression-free survival (PFS). Functionally, HDAC4 accelerated cell cycle G1/S transition and induced the epithelial-to-mesenchymal transition to promote NPC cell proliferation, migration, and invasion in vitro, as well as tumor growth and lung metastasis in vivo. Intriguingly, knockdown of N-CoR abolished the effects of HDAC4 on the invasion and migration abilities of NPC cells. Mechanistically, HDAC3/4 binds to the E-cadherin promoter to repress E-cadherin transcription. We also showed that the HDAC4 inhibitor tasquinimod suppresses tumor growth in NPC. Thus, HDAC4 may be a potential diagnostic marker and therapeutic target in patients with NPC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".